Security Implications of Big Data Strategies

Adrian Lane03/01/13

Security Implications of Big Data Strategies

Big data architectures and platforms are new, and they are evolving at a fantastic pace. Both commercial and open source development teams are releasing new features for their respective platforms every month. If one thing is for sure, it’s that today’s big data clusters — the platforms, features and bundles — will look very different from the data clusters we’ll see in the not-so-distant future. The security tools that scale to meet this new challenge will be different as well. We are very early in the adoption cycle for big data, but the earlier companies begin to tackle big data security, the easier the task will be. If security is a requirement for cluster development as it moves forward, clusters are less likely to be compromised by hackers. In addition, companies will dodge the painful experience of bolting half-baked security capabilities onto critical production infrastructure.

In this Dark Reading report, we will provide recommendations for how to approach the security of big data clusters. Along the way, we’ll address some of the common myths about big data and discuss some of the issues that make big data security more difficult than traditional relational database security projects. (S6680313)